摘要
随着我国大型工程建设项目数量增加,一系列涉及建设项目利益相关者的负面影响也随之凸现。因此,迫切需要对建设项目进行全面与客观的评价,以反映建设项目的综合满意度。文中提出了涉及到用户、投资者、业主、承包与供应商、政府以及项目周边组织在内的各利益相关者共19项指标组成的满意度评价指标体系,构建了具有强大的自适应、自组织、自学习能力及高度非线性映射性和泛化性特点的BP神经网络评价模型,并结合工程实例说明了具体应用。结果表明,该方法提高了建设项目满意度评价的可靠性和评价结果的有效性。
Along with the increase in the number of large-scale construction projects, a series of negative effects concerning various interest-related parts have emerged,which urges a comprehensive and objective evaluation of construction project so as to evaluate its overall satisfaction. In this paper,an evaluation indexes system of construction project satisfaction was advanced,which consists of 19 values coming from all main interest concerning parties, including users, investors, owners, suppliers, government and organizations nearby. A BP neural network evaluation model was built which was self-adaptive, self-organizing and self-study. And this evaluation model was applied to specific project ease. The result showed that this approach can improve the reliability and effectiveness of satisfaction evaluation of the construction project.
出处
《重庆建筑大学学报》
EI
CSCD
北大核心
2007年第4期125-128,共4页
Journal of Chongqing Jianzhu University
基金
国家建设部资助项目(06-R3-22)
关键词
BP神经网络
建设项目
满意度评价
BP neural network
construction project
satisfaction evaluation
